{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 卷积神经网络LeNet",
   "id": "c29bf21335fd997b"
  },
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-08-19T07:52:13.879704Z",
     "start_time": "2025-08-19T07:52:13.876770Z"
    }
   },
   "source": [
    "import time\n",
    "\n",
    "import torch\n",
    "from torch import nn\n",
    "from d2l import torch as d2l\n",
    "from utils_09 import load_data_fashion_mnist\n",
    "from utils_09 import Accumulator\n",
    "from utils_09 import accuracy"
   ],
   "outputs": [],
   "execution_count": 41
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-19T07:52:13.887708Z",
     "start_time": "2025-08-19T07:52:13.884709Z"
    }
   },
   "cell_type": "code",
   "source": [
    "class ReshapeLayer(torch.nn.Module):\n",
    "    '''定义通用图像预处理层，这里将传入的图像转为C1W28H28的tensor'''\n",
    "    def forward(self,x:torch.utils.data.DataLoader):\n",
    "        return x.reshape(-1,1,28,28)"
   ],
   "id": "5fe509e96ec94c53",
   "outputs": [],
   "execution_count": 42
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-19T07:52:13.893022Z",
     "start_time": "2025-08-19T07:52:13.890942Z"
    }
   },
   "cell_type": "code",
   "source": "device = torch.device('cuda')",
   "id": "c38d75fb5ca9f7c4",
   "outputs": [],
   "execution_count": 43
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-19T07:52:13.897175Z",
     "start_time": "2025-08-19T07:52:13.895027Z"
    }
   },
   "cell_type": "code",
   "source": "",
   "id": "cdcc255111944b7c",
   "outputs": [],
   "execution_count": null
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "使用$ \\frac{Input_h - Kernel_h + 2 * padding}{stride} + 1 $计算核处理后大小",
   "id": "780aae1802a0635a"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-19T07:52:13.916589Z",
     "start_time": "2025-08-19T07:52:13.908586Z"
    }
   },
   "cell_type": "code",
   "source": [
    "## 定义模型结构\n",
    "net = nn.Sequential(\n",
    "    ReshapeLayer(),\n",
    "    nn.Conv2d(in_channels=1,out_channels=6,kernel_size=5,padding=2), ## 设置输入通道为1，输出通道为6，卷积核为5*5 填充为2\n",
    "    nn.ReLU(),\n",
    "    nn.AvgPool2d(kernel_size=2,stride=2),## 设置池化核为2*2，步长为2\n",
    "    nn.Conv2d(in_channels=6,out_channels=16,kernel_size=5),\n",
    "    nn.ReLU(),\n",
    "    nn.AvgPool2d(kernel_size=2,stride=2),\n",
    "    nn.Flatten(),\n",
    "    nn.Linear(in_features=16*5*5,out_features = 120),\n",
    "    nn.ReLU(),\n",
    "    nn.Linear(in_features = 120,out_features = 84),\n",
    "    nn.ReLU(),\n",
    "    nn.Linear(84,10)\n",
    ")\n",
    "net.to(device)"
   ],
   "id": "3bccab017e9dffae",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sequential(\n",
       "  (0): ReshapeLayer()\n",
       "  (1): Conv2d(1, 6, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
       "  (2): ReLU()\n",
       "  (3): AvgPool2d(kernel_size=2, stride=2, padding=0)\n",
       "  (4): Conv2d(6, 16, kernel_size=(5, 5), stride=(1, 1))\n",
       "  (5): ReLU()\n",
       "  (6): AvgPool2d(kernel_size=2, stride=2, padding=0)\n",
       "  (7): Flatten(start_dim=1, end_dim=-1)\n",
       "  (8): Linear(in_features=400, out_features=120, bias=True)\n",
       "  (9): ReLU()\n",
       "  (10): Linear(in_features=120, out_features=84, bias=True)\n",
       "  (11): ReLU()\n",
       "  (12): Linear(in_features=84, out_features=10, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 44
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-19T07:52:13.960941Z",
     "start_time": "2025-08-19T07:52:13.921816Z"
    }
   },
   "cell_type": "code",
   "source": [
    "batch_size = 256\n",
    "train_iter , test_iter = load_data_fashion_mnist(batch_size,cpu_workers=4)"
   ],
   "id": "ad95a0a5c3eb0ee4",
   "outputs": [],
   "execution_count": 45
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-19T07:52:13.967332Z",
     "start_time": "2025-08-19T07:52:13.963946Z"
    }
   },
   "cell_type": "code",
   "source": [
    "def evaluate_accuracy_gpu(net:nn.Sequential,data_iter:torch.utils.data.DataLoader,device=None):\n",
    "    net.eval()\n",
    "    metric = Accumulator(2)\n",
    "    for X,y in data_iter:\n",
    "        X = X.to(device)\n",
    "        y = y.to(device)\n",
    "        metric.add(accuracy(net(X),y),y.numel())\n",
    "    return metric[0]/metric[1]"
   ],
   "id": "bd7edb1312c94302",
   "outputs": [],
   "execution_count": 46
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-19T07:52:13.975334Z",
     "start_time": "2025-08-19T07:52:13.971338Z"
    }
   },
   "cell_type": "code",
   "source": [
    "def init_weights(m):\n",
    "    if isinstance(m,nn.Linear) or isinstance(m,nn.Conv2d):\n",
    "        nn.init.xavier_normal_(m.weight)\n",
    "net.apply(init_weights)"
   ],
   "id": "5311108f3f4b661a",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sequential(\n",
       "  (0): ReshapeLayer()\n",
       "  (1): Conv2d(1, 6, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
       "  (2): ReLU()\n",
       "  (3): AvgPool2d(kernel_size=2, stride=2, padding=0)\n",
       "  (4): Conv2d(6, 16, kernel_size=(5, 5), stride=(1, 1))\n",
       "  (5): ReLU()\n",
       "  (6): AvgPool2d(kernel_size=2, stride=2, padding=0)\n",
       "  (7): Flatten(start_dim=1, end_dim=-1)\n",
       "  (8): Linear(in_features=400, out_features=120, bias=True)\n",
       "  (9): ReLU()\n",
       "  (10): Linear(in_features=120, out_features=84, bias=True)\n",
       "  (11): ReLU()\n",
       "  (12): Linear(in_features=84, out_features=10, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 47
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-19T08:05:58.314645Z",
     "start_time": "2025-08-19T07:52:13.979841Z"
    }
   },
   "cell_type": "code",
   "source": [
    "lr = 0.1\n",
    "optimizer = torch.optim.SGD(net.parameters(),lr = lr)\n",
    "loss = nn.CrossEntropyLoss()\n",
    "start_time = time.time()\n",
    "num_epochs = 100\n",
    "train_loss_record = list()\n",
    "train_acc_record = list()\n",
    "test_acc_record = list()\n",
    "for epoch in range(num_epochs):\n",
    "    metric = Accumulator(3)\n",
    "    net.train()\n",
    "    for X,y in train_iter:\n",
    "        optimizer.zero_grad()\n",
    "        X = X.to(device)\n",
    "        y = y.to(device)\n",
    "        y_predict = net(X)\n",
    "        l = loss(y_predict,y)\n",
    "        l.backward()\n",
    "        optimizer.step()\n",
    "        metric.add(l * X.shape[0],accuracy(y_predict,y),X.shape[0])\n",
    "    train_metric = (metric[0]/metric[2],metric[1]/metric[2])\n",
    "    test_acc = evaluate_accuracy_gpu(net,test_iter,device)\n",
    "    print(f\"epoch {epoch}, train loss : {train_metric[0]}, train acc : {train_metric[1]},test_acc : {test_acc}\")\n",
    "    train_loss_record.append(train_metric[0])\n",
    "    train_acc_record.append(train_metric[1])\n",
    "    test_acc_record.append(test_acc)\n",
    "elapsed_time = time.time() - start_time\n",
    "print(f'total elapsed {elapsed_time} seconds')"
   ],
   "id": "b17cbdc8513a6489",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 0, train loss : 1.0195660902659098, train acc : 0.6273333333333333,test_acc : 0.6927166666666666\n",
      "epoch 1, train loss : 0.5809987272898356, train acc : 0.7804833333333333,test_acc : 0.8137333333333333\n",
      "epoch 2, train loss : 0.4920076866149902, train acc : 0.8162,test_acc : 0.8119666666666666\n",
      "epoch 3, train loss : 0.44813861904144286, train acc : 0.8351166666666666,test_acc : 0.8408833333333333\n",
      "epoch 4, train loss : 0.4145920377731323, train acc : 0.8454166666666667,test_acc : 0.81395\n",
      "epoch 5, train loss : 0.39476750106811526, train acc : 0.8542,test_acc : 0.8344833333333334\n",
      "epoch 6, train loss : 0.3769574768066406, train acc : 0.8601333333333333,test_acc : 0.86505\n",
      "epoch 7, train loss : 0.3614803644816081, train acc : 0.8670166666666667,test_acc : 0.8660666666666667\n",
      "epoch 8, train loss : 0.3519031374613444, train acc : 0.86985,test_acc : 0.87\n",
      "epoch 9, train loss : 0.3411071489651998, train acc : 0.87395,test_acc : 0.8653\n",
      "epoch 10, train loss : 0.33109674803415934, train acc : 0.8769333333333333,test_acc : 0.8755833333333334\n",
      "epoch 11, train loss : 0.3246177910486857, train acc : 0.8786,test_acc : 0.8773\n",
      "epoch 12, train loss : 0.3182638350168864, train acc : 0.8811666666666667,test_acc : 0.8656\n",
      "epoch 13, train loss : 0.3091748011906942, train acc : 0.8842833333333333,test_acc : 0.8813166666666666\n",
      "epoch 14, train loss : 0.3048002795855204, train acc : 0.8857833333333334,test_acc : 0.8713\n",
      "epoch 15, train loss : 0.2987999359766642, train acc : 0.88845,test_acc : 0.8769\n",
      "epoch 16, train loss : 0.2933338151613871, train acc : 0.89135,test_acc : 0.8888833333333334\n",
      "epoch 17, train loss : 0.28756520926157636, train acc : 0.8933166666666666,test_acc : 0.8892\n",
      "epoch 18, train loss : 0.2823393571853638, train acc : 0.8949,test_acc : 0.8637\n",
      "epoch 19, train loss : 0.2771574556986491, train acc : 0.8969,test_acc : 0.8962833333333333\n",
      "epoch 20, train loss : 0.27388855962753295, train acc : 0.89755,test_acc : 0.8946666666666667\n",
      "epoch 21, train loss : 0.2703557853062948, train acc : 0.8983166666666667,test_acc : 0.89335\n",
      "epoch 22, train loss : 0.26471488796869913, train acc : 0.9004,test_acc : 0.88515\n",
      "epoch 23, train loss : 0.2615654854138692, train acc : 0.9019333333333334,test_acc : 0.8907833333333334\n",
      "epoch 24, train loss : 0.25637147464752197, train acc : 0.9042166666666667,test_acc : 0.8973666666666666\n",
      "epoch 25, train loss : 0.25354325675964356, train acc : 0.9052666666666667,test_acc : 0.9011166666666667\n",
      "epoch 26, train loss : 0.2518804549853007, train acc : 0.9060666666666667,test_acc : 0.9125333333333333\n",
      "epoch 27, train loss : 0.24723337548573812, train acc : 0.90625,test_acc : 0.8885166666666666\n",
      "epoch 28, train loss : 0.24256670770645142, train acc : 0.9089333333333334,test_acc : 0.8791166666666667\n",
      "epoch 29, train loss : 0.24261315517425538, train acc : 0.9077666666666667,test_acc : 0.9054166666666666\n",
      "epoch 30, train loss : 0.2389632921854655, train acc : 0.9104333333333333,test_acc : 0.90895\n",
      "epoch 31, train loss : 0.2328385998090108, train acc : 0.9126,test_acc : 0.9102\n",
      "epoch 32, train loss : 0.23076883891423544, train acc : 0.9139166666666667,test_acc : 0.9002166666666667\n",
      "epoch 33, train loss : 0.22782443787256876, train acc : 0.9143,test_acc : 0.91135\n",
      "epoch 34, train loss : 0.22457659543355307, train acc : 0.9153833333333333,test_acc : 0.9045333333333333\n",
      "epoch 35, train loss : 0.22164323774973552, train acc : 0.9169,test_acc : 0.9072333333333333\n",
      "epoch 36, train loss : 0.22057090932528178, train acc : 0.9167666666666666,test_acc : 0.9201166666666667\n",
      "epoch 37, train loss : 0.2141283176422119, train acc : 0.9194,test_acc : 0.9115833333333333\n",
      "epoch 38, train loss : 0.2141743387858073, train acc : 0.9195166666666666,test_acc : 0.9172333333333333\n",
      "epoch 39, train loss : 0.20999503660202026, train acc : 0.9201166666666667,test_acc : 0.9262166666666667\n",
      "epoch 40, train loss : 0.20728525511423745, train acc : 0.92175,test_acc : 0.92585\n",
      "epoch 41, train loss : 0.20599609540303548, train acc : 0.9221666666666667,test_acc : 0.9253166666666667\n",
      "epoch 42, train loss : 0.201859375222524, train acc : 0.9236166666666666,test_acc : 0.9056666666666666\n",
      "epoch 43, train loss : 0.20033369131088258, train acc : 0.92395,test_acc : 0.90675\n",
      "epoch 44, train loss : 0.19764037928581238, train acc : 0.9253166666666667,test_acc : 0.9199\n",
      "epoch 45, train loss : 0.19552458658218383, train acc : 0.9257166666666666,test_acc : 0.9214\n",
      "epoch 46, train loss : 0.19255295495986938, train acc : 0.9279666666666667,test_acc : 0.9193833333333333\n",
      "epoch 47, train loss : 0.19020345576604208, train acc : 0.9277166666666666,test_acc : 0.9246333333333333\n",
      "epoch 48, train loss : 0.18877148995399476, train acc : 0.9276166666666666,test_acc : 0.9315\n",
      "epoch 49, train loss : 0.1874344043413798, train acc : 0.9291833333333334,test_acc : 0.9161\n",
      "epoch 50, train loss : 0.18446285537083942, train acc : 0.93065,test_acc : 0.9169166666666667\n",
      "epoch 51, train loss : 0.18393124656677245, train acc : 0.93035,test_acc : 0.9322666666666667\n",
      "epoch 52, train loss : 0.18072653576533, train acc : 0.93075,test_acc : 0.93465\n",
      "epoch 53, train loss : 0.17736205066045124, train acc : 0.93315,test_acc : 0.9329666666666667\n",
      "epoch 54, train loss : 0.17687513222694398, train acc : 0.9338,test_acc : 0.9351166666666667\n",
      "epoch 55, train loss : 0.17506148544947306, train acc : 0.9332666666666667,test_acc : 0.9252333333333334\n",
      "epoch 56, train loss : 0.1730438749631246, train acc : 0.9339833333333334,test_acc : 0.9377833333333333\n",
      "epoch 57, train loss : 0.17114356009165446, train acc : 0.9363,test_acc : 0.929\n",
      "epoch 58, train loss : 0.16852410322825115, train acc : 0.9363,test_acc : 0.9243\n",
      "epoch 59, train loss : 0.16653079578081767, train acc : 0.9369333333333333,test_acc : 0.93125\n",
      "epoch 60, train loss : 0.16349751656850178, train acc : 0.9385166666666667,test_acc : 0.9189666666666667\n",
      "epoch 61, train loss : 0.16526751459439595, train acc : 0.9372166666666667,test_acc : 0.91555\n",
      "epoch 62, train loss : 0.16164306184450786, train acc : 0.9377833333333333,test_acc : 0.93315\n",
      "epoch 63, train loss : 0.15727530590693156, train acc : 0.94045,test_acc : 0.9350166666666667\n",
      "epoch 64, train loss : 0.15822507899602253, train acc : 0.9389833333333333,test_acc : 0.9255\n",
      "epoch 65, train loss : 0.15530686871210733, train acc : 0.9415666666666667,test_acc : 0.9302833333333334\n",
      "epoch 66, train loss : 0.15427807234128316, train acc : 0.9406333333333333,test_acc : 0.9285833333333333\n",
      "epoch 67, train loss : 0.15149091156323752, train acc : 0.9426333333333333,test_acc : 0.9449833333333333\n",
      "epoch 68, train loss : 0.14978947167396545, train acc : 0.94385,test_acc : 0.9403166666666667\n",
      "epoch 69, train loss : 0.14919243512153627, train acc : 0.9435166666666667,test_acc : 0.94555\n",
      "epoch 70, train loss : 0.1445381825129191, train acc : 0.9443,test_acc : 0.9400666666666667\n",
      "epoch 71, train loss : 0.14438011589050292, train acc : 0.9442833333333334,test_acc : 0.93525\n",
      "epoch 72, train loss : 0.14177241468429566, train acc : 0.9460166666666666,test_acc : 0.9416166666666667\n",
      "epoch 73, train loss : 0.14244310499827068, train acc : 0.9460166666666666,test_acc : 0.9497833333333333\n",
      "epoch 74, train loss : 0.13937813296318055, train acc : 0.9467166666666667,test_acc : 0.93215\n",
      "epoch 75, train loss : 0.13794386266072592, train acc : 0.9474333333333333,test_acc : 0.9420166666666666\n",
      "epoch 76, train loss : 0.13548759077390035, train acc : 0.9489166666666666,test_acc : 0.94545\n",
      "epoch 77, train loss : 0.13652284485499064, train acc : 0.94775,test_acc : 0.9400166666666666\n",
      "epoch 78, train loss : 0.13467938574155172, train acc : 0.9486833333333333,test_acc : 0.9520333333333333\n",
      "epoch 79, train loss : 0.1322443490187327, train acc : 0.9497833333333333,test_acc : 0.94815\n",
      "epoch 80, train loss : 0.13038871828715007, train acc : 0.9497666666666666,test_acc : 0.9466666666666667\n",
      "epoch 81, train loss : 0.12842228948275247, train acc : 0.9511,test_acc : 0.9467\n",
      "epoch 82, train loss : 0.129493692557017, train acc : 0.9511666666666667,test_acc : 0.94665\n",
      "epoch 83, train loss : 0.12503406132062275, train acc : 0.9522666666666667,test_acc : 0.9444166666666667\n",
      "epoch 84, train loss : 0.12919894402821858, train acc : 0.94975,test_acc : 0.9511\n",
      "epoch 85, train loss : 0.12227764395078024, train acc : 0.95295,test_acc : 0.9568333333333333\n",
      "epoch 86, train loss : 0.12094989538192749, train acc : 0.9541833333333334,test_acc : 0.9549666666666666\n",
      "epoch 87, train loss : 0.12012408480644227, train acc : 0.9544,test_acc : 0.92855\n",
      "epoch 88, train loss : 0.11985434737205505, train acc : 0.9546833333333333,test_acc : 0.9452166666666667\n",
      "epoch 89, train loss : 0.1172214233716329, train acc : 0.9554666666666667,test_acc : 0.9366333333333333\n",
      "epoch 90, train loss : 0.1190322825908661, train acc : 0.95485,test_acc : 0.9531333333333334\n",
      "epoch 91, train loss : 0.1157213759581248, train acc : 0.95565,test_acc : 0.9529\n",
      "epoch 92, train loss : 0.11328772470156352, train acc : 0.9570833333333333,test_acc : 0.9190833333333334\n",
      "epoch 93, train loss : 0.11291910196940104, train acc : 0.9581833333333334,test_acc : 0.9534333333333334\n",
      "epoch 94, train loss : 0.11351635835965475, train acc : 0.9563333333333334,test_acc : 0.95385\n",
      "epoch 95, train loss : 0.11002648289203644, train acc : 0.9578666666666666,test_acc : 0.9602333333333334\n",
      "epoch 96, train loss : 0.10889539709091187, train acc : 0.9592666666666667,test_acc : 0.9448333333333333\n",
      "epoch 97, train loss : 0.11094063440958658, train acc : 0.9573333333333334,test_acc : 0.9529\n",
      "epoch 98, train loss : 0.10702010445594788, train acc : 0.9596333333333333,test_acc : 0.9001166666666667\n",
      "epoch 99, train loss : 0.10673043166796366, train acc : 0.9605833333333333,test_acc : 0.9573666666666667\n",
      "total elapsed 824.3287935256958 seconds\n"
     ]
    }
   ],
   "execution_count": 48
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-19T08:07:04.872469Z",
     "start_time": "2025-08-19T08:07:04.747402Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from matplotlib import pyplot as plt\n",
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot(131)\n",
    "ax1.plot(range(num_epochs),train_acc_record)\n",
    "ax1.set_xlabel('epoch')\n",
    "ax1.set_ylabel('acc')\n",
    "ax2 = fig.add_subplot(132)\n",
    "ax2.plot(range(num_epochs),train_loss_record)\n",
    "ax2.set_xlabel('epoch')\n",
    "ax2.set_ylabel('loss')\n",
    "ax3 = fig.add_subplot(133)\n",
    "ax3.plot(range(num_epochs),test_acc_record)\n",
    "ax3.set_xlabel('epoch')\n",
    "ax3.set_ylabel('test acc')\n",
    "plt.show()"
   ],
   "id": "83e87e4584683aad",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 49
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-19T08:45:19.101804Z",
     "start_time": "2025-08-19T08:45:14.731140Z"
    }
   },
   "cell_type": "code",
   "source": [
    "for X, y in test_iter:\n",
    "    break\n",
    "def get_mnist_labels(labels:list[int]) -> list[str]:\n",
    "    \"\"\"返回mnist数据集标签文本\"\"\"\n",
    "    text_labels = ['t-shirt','trouser','pullover','dress','coat','sandal','shirt','sneaker','bag','ankle boot']\n",
    "    return [text_labels[int(i)] for i in labels]\n",
    "X = X[0:10].to(device)\n",
    "net.eval()\n",
    "with torch.no_grad():\n",
    "    y_hat = net(X[:10])\n",
    "pred_indexs = y_hat.argmax(axis=1).cpu().numpy()\n",
    "true_index = y.numpy()\n",
    "# 可视化\n",
    "pred_titles = get_mnist_labels(pred_indexs)\n",
    "true_titles = get_mnist_labels(true_index)\n",
    "images = X[:10].cpu().reshape(10, 28, 28)\n",
    "\n",
    "figsize = (10 * 20, 1 * 70)\n",
    "_, axes = plt.subplots(10, 1, figsize=figsize)\n",
    "axes = axes.flatten()\n",
    "for i, (ax, img) in enumerate(zip(axes,images)):\n",
    "    ax.imshow(img.numpy(),cmap='gray')\n",
    "    ax.set_title(f\"Pred: {pred_titles[i]}\\nTrue: {true_titles[i]}\")"
   ],
   "id": "9d4402af76343ae6",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 20000x7000 with 10 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 71
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
